[D] Is there any way to perform incremental matrix factorization on a Surprise SVD model?

I have a pre trained SVD model, however, when i get a user's data and want to add it to the data set for a recommendation, i dont want to fit the model all over as it is computationally complex and time consuming. I have seen that there are methods of performing incremental matrix factorization which allows for the fitting of just the new data without disturbing the learning of the pretrained model. Is this available using the surprise library …

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